The subject matter disclosed herein relates to site surveying, and more particularly, to the autonomous collection of multi-sensory data around an industrial asset for building a three-dimensional model of the asset and its environment. It would be desirable for robots, especially those operating in industrial environments, to have the ability to sense and model their environment autonomously. This model of the environment can then be used to direct other tasks such as inspection, obstacle avoidance, robot localization, and targeting.
Many existing 3D reconstruction systems suffer from several limitations that affect their performance. Typically, the data required for the three-dimensional (3D) reconstruction of assets is collected either by a drone flown manually by a human operator or by a sensing system carried by a human. Note that having a human carry out aspects of the data collection process can be a difficult and error-prone task. This can be especially true when planned data collection will take a substantial amount of time, the collection can potentially take various routes, there are many points of interest to be examined, the asset and/or surrounding environment are complex and dynamically changing, other people and/or robots are simultaneously operating in the area, etc.
Manual data collection provides no assurances that the right data has been collected to generate a 3D reconstruction that meets certain Key Performance Indicators (KPIs) such as ensuring that the images are in focus, directed at the right region of the asset, and have enough overlap across images to build an accurate model. Moreover, manual data collection usually leads to the collection of a large amount of data. As discussed above, currently available systems typically involve a human operator flying a drone manually to capture a large number of images (e.g., in the order of thousands) which are then used to build a 3D model of the asset. Feeding this entire data set to a reconstruction engine can be very computationally expensive. Furthermore, the presence of images that are not in focus or do not have sufficient overlap can lead to degraded reconstruction.
It would therefore be desirable to provide systems and methods to facilitate three-dimensional robotic site surveying in an automatic and adaptive manner.